Abstract book (pdf) - ICPR 2010

13:30-16:30, Paper ThBCT8.63
The Problem of Fragile Feature Subset Preference in Feature Selection Methods and a Proposal of Algorithmic
Workaround
Somol, Petr, Inst. of Information Theory and Automation, Czech
Grim, Jiří, Inst. of Information Theory and Automation
Pudil, Pavel, Prague Univ. of Ec.
We point out a problem inherent in the optimization scheme of many popular feature selection methods. It follows from
the implicit assumption that higher feature selection criterion value always indicates more preferable subset even if the
value difference is marginal. This assumption ignores the reliability issues of particular feature preferences, over-fitting
and feature acquisition cost. We propose an algorithmic extension applicable to many standard feature selection methods
allowing better control over feature subset preference. We show experimentally that the proposed mechanism is capable
of reducing the size of selected subsets as well as improving classifier generalization.
ThBCT9 Lower Foyer
Signal, Speech, and Image Processing Poster Session
Session chair: Ariki, Yasuo (Kobe Univ.)
13:30-16:30, Paper ThBCT9.1
Removing Partial Occlusion from Blurred Thin Occluders
Mccloskey, Scott, McGill Univ. Honeywell
Langer, Michael, McGill Univ.
Siddiqi, Kaleem, McGill Univ.
We present a method to remove partial occlusion that arises from out-of-focus thin foreground occluders such as wires,
branches, or a fence. Such partial occlusion causes the irradiance at a pixel to be a weighted sum of the radiances of a
blurred foreground occluder and that of the background. The result is that the background component has lower contrast
than it would if seen without the occluder. In order to remove the contribution of the foreground in such regions, we characterize
the position and size of the occluder in a narrow aperture image. In subsequent images with wider apertures, we
use this characterization to remove the contribution of the foreground, thereby restoring contrast in the background. We
demonstrate our method on real camera images without assuming that the background is static.
13:30-16:30, Paper ThBCT9.2
A New Approach to Aircraft Surface Inspection based on Directional Energies of Texture
Mumtaz, Mustafa, National Univ. of Sciences and Tech.
Bin Mansoor, Atif, National Univ. of Sciences and Tech.
Masood, Hassan, National Univ. of Sciences and Tech.
Non Destructive Inspections (NDI) plays a vital role in aircraft industry as it determines the structural integrity of aircraft
surface and material characterization. The existing NDI methods are time consuming, we propose a new NDI approach
using Digital Image Processing that has the potential to substantially decrease the inspection time. The aircraft imagery is
analyzed by two methods i.e Contourlet Transform (CT) and Discrete Cosine Transform (DCT). With the help of Contourlet
Transform the two dimensional (2-D) spectrum is divided into fine slices, using iterated directional filter banks. Next, directional
energy components for each block of the decomposed subband outputs are computed. These energy values are
used to distinguish between the crack and scratch images using the Dot Product classifier. In next approach, the aircraft
imagery is decomposed into high and low frequency components using DCT and the first order moment is determined to
form feature vectors. A correlation based approach is then used for distinction between crack and scratch surfaces. A comparative
examination between the two techniques on a database of crack and scratch images revealed that texture analysis
using the combined transform based approach gave the best results by giving an accuracy of 96.6% for the identification
of crack surfaces and 98.3% for scratch surfaces.
13:30-16:30, Paper ThBCT9.3
A Generalized Anisotropic Diffusion for Defect Detection in Low-Contrast Surfaces
Chao, Shin-Min, Utechzone Co. Ltd.
Tsai, Du-Ming, Yuan-Ze Univ.
Li, Wei-Chen, Yuan-Ze Univ.
Chiu, Wei-Yao, Yuan-Ze Univ.
- 314 -